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Achievements

Achievement: Arctic Code Vault ContributorAchievement: Starstruckx3Achievement: Pull Shark

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ayooshkathuria/README.md

👋 Hi, I'm Ayoosh!

AI Researcher & RL Practitioner diving deep into LLMs and exploring how RL can enhance them. Passionate about AI, optimization & making models smarter! 🤖🔥

🏆 Work Experience

🔍 DRDO – Object detection for video surveillance in defense.
🎨 Pix2PixHD GAN – High-res image-to-image translation in MATLAB. 🔗
🚗 IIIT-Delhi – RL for mixed-autonomy traffic optimization.
❄️ Phaidra – RL for industrial cooling (Alpha Zero, MuZero, AWAC, PPO).

🛠️ Notable Projects

🦙 Llama 3.2 – Fine-tuning from scratch on Alpaca-style datasets.
🖼️ Computer Vision Augmentation Library – Bounding box augmentation for object detection.
🔥 PyTorch from Scratch – Step-by-step tutorial.

✍️ Writings

📜 Paperspace Blog – AI articles
✍️ Medium – More of my work

📬 Connect with Me

📧 Email: kathuria.ayoosh@gmail.com
💼 LinkedIn: Ayoosh Kathuria
🐦 X (Twitter): @KathuriaAyoosh

🚀 Always open to exciting AI collaborations & discussions!

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  1. Llama-3.2-FT-From-Scratch-Alpaca Llama-3.2-FT-From-Scratch-Alpaca Public

    A project that implements Llama 3.2 from scratch and finetunes it on Alpca-style data.

    Jupyter Notebook

  2. pytorch-yolo-v3 pytorch-yolo-v3 Public

    A PyTorch implementation of the YOLO v3 object detection algorithm

    Python 3.3k 1.1k

  3. YOLO_v3_tutorial_from_scratch YOLO_v3_tutorial_from_scratch Public

    Accompanying code for Paperspace tutorial series "How to Implement YOLO v3 Object Detector from Scratch"

    Python 2.3k 726

  4. Paperspace/DataAugmentationForObjectDetection Paperspace/DataAugmentationForObjectDetection Public

    Data Augmentation For Object Detection

    Jupyter Notebook 1.1k 317

  5. Paperspace/PyTorch-101-Tutorial-Series Paperspace/PyTorch-101-Tutorial-Series Public

    PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.

    Jupyter Notebook 258 58

  6. kmeans_vectorised_v2.py kmeans_vectorised_v2.py
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    import numpy as np
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    import matplotlib.pyplot as plt
    3 
    import random
    4 
    import time
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    7.